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Transcriptomic responses to acute or chronic ethanol exposure observed across five brain regions in male mice

GSE314324 Mus musculus (mouse) RNA-seq (gene expression) 62 samples Submitted 2026/03/30 Platform GPL34475Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 62 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
62 samples: 20 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Epigenetic and Transcriptomic Impacts of Ethanol Vary by Brain Region and Extent of ExposureeNeuro · 2026
Summary (written by the submitters)
Alcohol use disorder (AUD) has been consistently linked to transcriptomic dysregulation in the brain. Alcohol itself produces transcriptomic changes in the brain, and resulting molecular changes may contribute to the progression or maintenance of AUD. However, little is known about how ethanol-induced transcriptomic outcomes differ between acute and chronic exposure.
Read the full summary ↓
Here, we systematically investigated the transcriptomic effects of ethanol exposure across key brain regions relevant to AUD and how these outcomes differ between acute and chronic exposure. To this end, RNA sequencing was done for the cortex, dorsal hippocampus, ventral hippocampus, dorsal striatum, and ventral striatum of adult male mice that were given a daily i.p. dose of ethanol or saline for 1 day (acute) or 10 days (chronic). Both ethanol exposure paradigms resulted in dysregulated expression (gene and transcript) and splicing in the investigated brain regions. Transcriptomic dysregulation varied across regions and was more robust following acute than chronic ethanol exposure. Paradigm-dependent transcriptional effects of ethanol were limited in most regions but were striking in the ventral hippocampus, suggesting alcohol's transcriptomic effects in this region might play a relevant role in the transition from limited to chronic alcohol consumption. Overall, this systematic study illuminates alcohol's effects on transcriptional regulation in the brain and how these effects differ across brain regions and by extent of exposure, ultimately providing valuable insight for developing novel therapeutics for AUD.
Published in
Epigenetic and Transcriptomic Impacts of Ethanol Vary by Brain Region and Extent of Exposure
Periandri EM, Dodson KM, Lopes M et al. · eNeuro 2026 · PMID 41912333 · doi:10.1523/ENEURO.0484-25.2026
This dataset
Open GSE314324 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE314324_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1390714 and SRA study SRP656453. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41912333) ↗
Study design
20 conditions, mostly in triplicate
RNA_AE_dHPC ×4 RNA_CE_DS ×4 RNA_AP_CTX ×3 RNA_AE_CTX ×3 RNA_AP_dHPC ×3 RNA_AP_vHPC ×3 RNA_AE_vHPC ×3 RNA_AP_DS ×3 +12 more

Supports a between-group comparison across 62 samples.

How we read this: 20 replicated groups read from 62 sample titles; they account for 62 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 22 more — browse all 62 samples with per-sample file links →

Datasets on a similar topic

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